Forskningsprosjektet "Digital Infrastructure for Robust and Scalable Patient Monitoring in Pandemic Response Situations" handler om digital oppfølging av pasienter med symptomer på infeksjoner, som for eksempel Covid-19. Det antas at digital hjemmeoppfølging vil gi flere typer effekter: Pasienter med symptomer kan føle seg trygge hjemme, man kan minske behovet for sykehusinnleggelser, og helsepersonell som er i karantene kan arbeide hjemmefra. Forskningsprosjektet har støttet opp under helsetjenestens evaluering av hvordan et slikt tilbud har fungert. Gjennom å involvere både pasienter og helsepersonell har vi bidratt til forbedringer og videreutvikling av løsninger og tjenester. Forskere fra Senter for e-helse ved UiA samarbeider med kommunene i Agder, Sørlandet Sykehus, IKT-klyngen Digin, I4Helse AS, Siemens Healthcare og Medsensio for å utforske mulighetene omkring digitalt undertøttede oppfølgingstjenester. Målet er å bruke mulighetene i digitalt understøttede oppfølgingstjenester til å være bedre forberedt på neste pandemi.
Digital home monitoring, where patients at home register vital signs which are monitored by health personnel, were used during the Covid19 pandemic. This allowed Covid patients to feel safer at home, reduced the demand for hospital admission, and allowed quarantined health personnel to work remotely. The technical solutions used in Norway were mainly repurposed from other usage areas, and the research project has supported the evaluation of digital home monitoring specifically for pandemic situations, which saw novel user groups and service models. We have conducted evaluations based on a) usability assessments focusing on how Universal Access standards would increase the availability of the solution for diverse user groups, b) conducted two studies with patient users to gather experiences and suggestions, c) conducted two studies with healthcare personnel to gather experiences and suggestions, and d) a broader study with citizens and health personnel to gather perceptions and attitudes from potential users (i.e., respondents who had not themselves necessarily been users). These studies resulted in recommendations for redesign of the existing solution, as well as for quality assurance and improvement of the service models.
We also explored the infrastructural preconditions for utilizing digital home monitoring more effectively. This resulted in description of integration requirements to both front-end (third-party data collection devices) and back-end systems (electronic patient record systems). Such integrations will be necessary if a future solution should be able to collect data at a scale and if the data should be used not only for real-time monitoring of individual patients, but as a source of data-driven learning (as unique data from the initial disease stages may, when combined with data from clinical information systems will allow the development of novel clinical knowledge on severity, disease progression and outcomes, which will be useful for treatment processes and forward triage). We explored the experiences reported in the research literature of automating patient monitoring using artificial intelligence/data analytic approaches. As this can be controversial and ethically challenging, we have conducted a large-scale survey to learn about the attitudes and preferences of both health care personnel and citizens. While the preference was for human-supported monitoring in both groups, there was a large minority where automated monitoring was viewed favourably (larger among citizens than healthcare personnel). Such future-oriented capabilities (most of which are still unrealized) may make the digital home-monitoring infrastructure better prepared for the next pandemic. In sum, this project has generated knowledge that will help build a stronger digital infrastructure and health system both in a short-term and long-term perspective.
This research project targets digitally supported services for home-monitoring of patients in an epidemic or pandemic situation, including patients with suspected or verified COVID-19 infection. Such solutions, which was rapidly made available at the outbreak of the Covid19 pandemic, allows patients’ self-reporting of symptoms to be transferred to clinicians who follow up the progression of the disease. An existing platform for digital home monitoring of patients with chronic diseases was used, however, the situation of a pandemic poses novel demands. Our overall research question is: Which novel capabilities are required when designing home-monitoring services for forward triaging and remote care in a pandemic usage situation?. This will be answered through both evaluative and exploratory research.
We will conduct a feasibility study and an evaluation of services to provide quality assurance and identify areas for improvement. Further, we seek to establish the required infrastructural capabilities to allow capture of the unique, patient-reported, early-phase disease data coming from digitally supported monitoring, including third-party solutions (e.g. IoT and wearables). We will also explore the possibility to combine patient monitoring services with e.g. predictive models, assistive intelligence and AI-enabled automation.To complement this, investigations of ethical, practical and regulatory aspects will be conducted, as well as surveys to find out the opinions and preferences of both citizens and health workers. An analysis of the health actors’ response to the pandemic and their decisions to utilize (or not) digital technologies for home monitoring will be studied from an organizational innovation perspective, giving insights on how learnings during the pandemic may contribute to future innovation culture and responsiveness.